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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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Based on deep convolutional neural network, COVID-19 identification utilizing computed tomography scans Yonan, Janan Farag; Fadheel, Fadil Raafat; Al-Doori, Mohammed A. J. Hammeid; Ali, Adnan Hussein
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5124

Abstract

In the year 2019 specifically, on March 11th, the coronavirus illness two thousand nineteen (COVID-19) was announced a worldwide epidemic due to its rapid spread and lack of treatment options. As a result, infected individuals must be identified and quarantined quickly to prevent the illness from spreading. The method used to test for COVID-19 is called real-time-polymerase chain reaction (RT-PCR), which has problems with having low sensitivity and taking an extended amount of time. Because chest computed tomography (CT) scans are more sensitive than RT-PCR, it follows that such scans can be employed for diagnostic purposes. This study developed a deep convolutional neural network (CNN) approach to detect COVID-19 using CT scan images. An architecture of deep learning (DL) called convolutional neural network computed tomography scans (CT-CNN) was utilized to efficiently identify COVID-19. The findings of our suggested model are highly encouraging, with an accuracy of 96.14%, an F1 score of 96.21%, and a recall of 97.53% when it comes to classifying CT scans as either infected or not infected by COVID-19.
A comprehensive achievement investigation of iterative mean filter for outlier extinguish aspiration on ubiquitous FVIN Patanavijit, Vorapoj; Thakulsukanant, Kornkamol
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5951

Abstract

Under commonwealth of the outlier extinguish inspection, exclusively on the impulsive outlier, the outlier extinguish algorithm is a substantial step, which is early performed prior to further computer vision steps thereupon the iterative mean filter (IMF) is inaugurated for fix value impulsive noise (FVIN) and grown into one of the superior achievement outliers extinguish algorithms. This academic article focuses to investigate the correlative achievement of the outlier extinguish algorithm established on IMF, is inaugurated from mean filter (MF) for carrying out the poor achievement of the aforesaid outlier extinguish algorithms (standard median filter (SMF), MF, and adaptive median filter (AMF)), for FVIN at omnipresent scattering of outlier consistency (5-90%). The analytical experiment comprehensively exploits on bountiful figures (F16, Girl, Lena, and Pepper) that are inspected in order to analyze the correlative achievement of an outlier extinguish algorithm established on IMF. In contrast with the aforesaid outlier extinguish algorithms (SMF, MF, and AMF), the outlier extinguish algorithm established on IMF has superior achievement from the experimental results.
Portable internet of things-based soil nutrients monitoring for precision and efficient smart farming Hartono, Rudi; Maulana Yoeseph, Nanang; Aji Purnomo, Fendi; Asri Safi'ie, Muhammad; Alim Tri Bawono, Sahirul
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7928

Abstract

This paper describes the design and implementation of a portable internet of things (IoT)-based system for online monitoring of soil nutrients, specifically nitrogen (N), phosphorus (P), and potassium (K), to improve precision and efficiency in smart farming. The main goal is to use IoT technology to analyze soil conditions on-site and provide advice about fertilization and soil management. The system measures soil nutrient levels using field-based sensors, such as an NPK probe, and transmits data over a wireless sensor network. The research comprises a quantitative evaluation of the performance of the IoT system using various sensors. An analysis of variance (ANOVA) was used to compare the accuracy of the IoT device with industrial soil nutrient measurement equipment, demonstrating differences in P and K values but not in N values. This disparity points to certain areas where the accuracy of the P and K measurements in the IoT system should be improved. This IoT-based soil nutrient monitoring system highlights the potential of smart farming technology to boost agricultural output, optimize resource consumption, and support sustainable farming practices. The system's portability and online data availability provide farmers with exact soil condition information, allowing them to make more efficient and intelligent farming decisions.
Performance comparison of state-of-the-art deep learning model architectures in Indonesian food image classification Rasyidi, Mohammad Arif; Mardhiyyah, Yunita Siti; Nasution, Zuraidah; Wijaya, Christofora Hanny
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7996

Abstract

Food image recognition is essential for developing an elderly-friendly daily food recording application in Indonesia. However, existing datasets and models are limited and do not cover the diversity and complexity of Indonesian food. In this paper, we present a new dataset of 24,427 images of 160 types of Indonesian food with higher variety and quality than previous datasets. We also train and compare the performance of 67 models based on 16 state-of-the-art deep learning architectures on this dataset. We find that efficientnet_v2_l provides the best accuracy of 85.44%, followed by other models such as convnext_large and swin_s. We also discuss the trade-off between model size and performance, as well as the challenges and limitations of food image classification. Our dataset and models can serve as a basis for developing a user-friendly and accurate food recording application for the elderly population in Indonesia.
An improved dual vector control for a doubly fed induction generator based wind turbine during asymmetrical voltage dips Moumani, Youssef; Jabal Laafou, Abdeslam; Ait Madi, Abdessalam; Boutssaid, Rachid
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7969

Abstract

This paper introduces a robust and inhanced version of dual control approach based on sequence decomposition loops in order to limit transient over-currents and improving the wind turbine’s operation during asymmetrical voltage dips faults. Indeed, the doubly fed induction generator (DFIG), employed in wind energy conversion system (WECS) to produce electrical energy from wind, highly susceptible to voltage drops, which can cause transient overcurrents in both the stator and the rotor. Without any protection system, these over-currents might damage the DFIG and its converters. The strategy put forward in this work minimizes the consequences of voltage dips on wind system functioning, such as electromagnetic torque fluctuations and it enables wind turbines to maintain electrical connection with the grid in the occurrence of such disturbances. The carried-out results are promising and showed that the proposed control method can effectively minimise the oscillations in electromagnetic torque, reactive power and DC bus voltage during the asymmetrical voltage dip. This analysis also demonstrated its ability to limit the transient over-currents of the DFIG.
TBNet: learning from scratch and limited training data, a CNN based tuberculosis bacilli detection Agoes, Ali Suryaperdana; Winarno, Winarno
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5279

Abstract

Tuberculosis (TB) is an infectious disease caused by the micro-bacteria. Several studies that have been conducted previously aimed to reduce the burden of observing tuberculosis bacilli using the digital image processing method. In this study, we proposed a newly developed convolutional neural network (CNN) based deep learning model to detect tuberculosis bacilli in sputum smear images. Recent advances in deep learning apply large scale image dataset to achieve convergent weight model. However, medical image dataset commonly available in relatively small quantity. In contrary with common deep learning approach, our model is capable to learn from our small dataset which consist of highly diverse hue and contrast of sputum smear images. Furthermore, its performance is proven to be reliable to detect sputum smear image content, which are TB bacillus and debris.
A discernment of round-robin vs SD-WAN load-balancing performance for campus area network Gamilla, Anazel P.; Tolentino, Anjela C.; Payongayong, Reina T.
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.5945

Abstract

Efficient load balancing is crucial for optimizing network performance and ensuring seamless connectivity in modern campus area networks (CANs). With the proliferation of data-intensive applications and the increasing reliance on cloud-based services, organizations are seeking effective load-balancing solutions to distribute network traffic evenly across available resources. The continuous improvement of devices, tools, and techniques to cater a large amount of network traffic, started to be employed on different campuses. Understanding the best approach to maximize the utilization of the network resources is crucial in order to stabilize and maintain the network. The study aims to discern the round-robin and software defined-wide area network (SD-WAN) techniques based on defined metrics and conducted with a predefined payload for commonly used application conditions. The analysis shows that SD-WAN delivers a much superior performance than round-robin based on the criteria. The local area network (LAN) test shows difference between the two types of technology for the three given metrics. The WAN test shows that the round-robin has higher packet loss, latency, and jitter than the SD-WAN technology. While round-robin may suffice for small-scale deployments with relatively homogeneous traffic patterns, SD-WAN offers more sophisticated capabilities for larger CANs with diverse application workloads and distributed locations.
Wastewater monitoring system in the textile industry Raditya, Murry; Pratama, I Putu Eka Widya; Bagastyo, Arseto Yekti; Nurhayati, Ervin; Kalahari, Bintang
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7220

Abstract

Recently, a problem which often experienced by the Environmental Agency is to monitor the quality of industrial waste. The problem comes from manual monitoring of wastewater and the high cost of laboratory tests for each variable for the waste. This system is intended to develop a wastewater monitoring system considering the state of the environment and technology. This system uses 5 types of sensors to measure the quality of wastewater. The sensor will display measurement data both offline via liquid crystal display (LCD) and online via the website. For the pH sensor test, we obtained an error value approximately of 1.32% and accuracy of 98.68%. For the oxidation reduction potential (ORP) sensor test, we obtained an error value of 1.4% with 98.6% accuracy. We obtained an error value of 0.22% with 99.78% accuracy for the temperature sensor test. For the total dissolved solid (TDS) sensor test, we obtained an error value of 1.02% with 98.98% accuracy. The color sensor is validated using a spectrometer to measure the variation of color in remazol waste concentration. For the Client - Server communication test, the system has a delay of 2 seconds. One of the advantages of using a web server is the system has minimum network traffic.
Frequency response of microgrids with PV power generation and energy storage system (battery and supercapacitor) Hamzah Abdullah, Alaa; M. Al-Anbary, Karrar; Mahdi Hamad, Qasim; Ali Al Abboodi, Hanaa Mohsin; Taih Gatte, Mohammed
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5071

Abstract

Since renewable energy sources (RES) have almost little inertia, an increase in their electricity might harm the power system's ability to run steadily and dependably. Numerous solutions to the issue mentioned above are offered. This paper aims to assess the technological possibility of using energy storage system (ESS) devices built from batteries and supercapacitors to enhance the interia response of sources in microgrids with a large amount of PV power penetration. The microgrid's inertia was altered by varying the penetration level of RES. To obtain a rigid microgrid, batteries and supercapacitors are suggested in this study to enhance frequency stability and droop control is utilized to complete this assessment. The model of the on-grid power network was designed using Simulink in MATLAB to evaluate the high level of RES penetration impact on the frequency stability of the system. Results verify that the microgrid stiffness is significantly enhanced when the suggested storage elements are incorporated. The findings show that the rate of change of frequency (RoCoF) is reduced when the size of the ESS increases and vice versa. The supercapacitor energy storage system (SCESS) can increase the stability of the system's frequency more effectively than the battery energy storage systems (BESS) with a slower time response.
Mobile application: awareness of the population on the environmental impact Andrade-Arenas, Laberiano; Giraldo-Retuerto, Margarita; Molina-Velarde, Pedro; Yactayo-Arias, Cesar
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6131

Abstract

Nowadays, pollution keeps increasing due to social, political, economic, cultural, and environmental factors. Environmental awareness is close to zero because people prioritize personal activities. In that sense, the objective of this investigation is to raise environmental awareness in the population regarding the impact of pollution and support this through a mobile application (APP) that helps reduce pollution. The methodology used was the cascade, and through its phases, it was developed the prototype design of the mobile APP. The results obtained from this hybrid research were through a survey using ATLAS.ti 22; it concluded that environmental awareness begins at home and is taught by the parents, also it should be promoted from elementary school to high school and even in college. Moreover, in a survey, the users stated by 89% that the use of this mobile APP can help reduce the environmental impact. Also, in the validation through expert judgment, all the attributes were accepted with an average of 81%, that of functionality was the lowest, and the highest was that of consistency and integration with 83%. Finally, environmental education should be a priority policy in any country, as this will benefit its population.

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